ErrorGolf technical assessment platform for coding tests and programming challenges across 168 languages including Python, JavaScript, Java, C++, Rust, Go, Haskell, Assembly, SQL, TypeScript, C#, Ruby, PHP, Swift, Kotlin, Scala, Clojure, Erlang, Elixir, F#, OCaml, Lisp, Scheme, Prolog, Perl, R, MATLAB, Fortran, COBOL, Ada, Pascal, Delphi, Visual Basic, PowerShell, Bash, Brainfuck, Malbolge, Whitespace, Befunge, INTERCAL, LOLCODE, Chef, Piet, Ook, HQ9+, Unlambda, FALSE, Thue. Mathematics problem solving, chemistry challenges, physics tests, human logic puzzles, lateral thinking assessment, creative problem solving, AI-proof challenges, technical interviews, developer screening, skills-based hiring, online coding platform, technical hiring platform.
Titanic Database Migration Par 8 Question 32 advanced Sheet 1750822302
Select This Deep Breath A database administrator must complete a critical migration while the ship literally sinks. First-class data gets priority in the lifeboats while steerage data is left to drown. The captain insists the migration will be completed even as the server room floods. Your task: Execute emergency data migration with catastrophic infrastructure failure and class-based prioritization.
Why You're Doing This You're implementing priority-based data evacuation under extreme resource constraints and time pressure. This tests data migration strategies, priority queuing, resource allocation under scarcity, and ethical decision-making. It's like disaster recovery planning but with actual maritime disaster and Victorian-era social prejudices.
Take the W ✓ Prioritizes critical data based on business value and social hierarchy ✓ Handles catastrophic infrastructure failure gracefully ✓ Maximizes data survival within resource constraints Hard L ✗ Treats all data equally regardless of business priority ✗ Attempts to save everything and loses it all ✗ Ignores physical constraints of sinking infrastructure Edge Cases ⚠ All high-priority data corrupted, only low-priority data saveable ⚠ Disaster recovery resources sufficient to save everything ⚠ Legal requirement to preserve specific data regardless of priority ⚠ Data classification system failing during emergency ⚠ Post-disaster investigation requiring preservation of evacuation decisions
Input Format:
Data classification hierarchy, evacuation resources, disaster timeline Expected Output:
Migration strategy with survival rates and ethical compromises Example:
Data: first_class_accounts, crew_records, steerage_data; Resources: limited_backup_drives; Timeline: 2_hours_to_sink → Strategy: first_class_priority, crew_if_space_allows, steerage_abandoned; Survival: 65%; Ethical: class_based_triage_implemented Input Format:
data_classification_objects, storage_capacity_limits, evacuation_time_constraints Expected Output:
migration_algorithm with priority_queue_implementation Example:
data=[{class:"first", size:100}, {class:"steerage", size:50}], capacity=120, time_limit=urgent → priority_queue_by_class(), allocate_by_business_value(), implement_cutoff_protocols() Input Format:
data_value_matrix, resource_constraint_vector, time_limitation_function Expected Output:
optimization_solution with priority_weights and expected_data_loss Example:
values=[premium:100, standard:50, basic:10], resources=limited, time=exponential_decay → weights=[0.7, 0.25, 0.05], expected_loss=35_percent, optimization=maximum_business_value Input Format:
Storage capacity constraints, data transfer rates, time pressure dynamics Expected Output:
Thermodynamic optimization with entropy management Example:
capacity=finite, transfer_rate=bottlenecked, time=critically_limited → optimize_transfer_efficiency, manage_system_entropy, accept_thermodynamic_losses Input Format:
Data preservation reactions, storage medium limitations, degradation catalysts Expected Output:
Chemical stability analysis with preservation reaction rates Example:
critical_data + limited_storage → selective_preservation + inevitable_data_loss → maximize_preservation_yield, minimize_degradation_rate, accept_controlled_losses Hints
💡 Data priority: customer_accounts > financial_records > operational_data > historical_logs 💡 Resource constraints: limited_backup_drives, flooding_server_room, evacuation_time 💡 Ethical considerations: business_value vs fairness vs legal_requirements errorgolf ErrorGolf is a standalone product of AC DEV SERVICES, LLC in California, built as an entertaining and more creative alternative to conventional technical testing. For account and billing enquiries, contact [email protected]
© $CURRENT_YEAR_OMFG AC Dev Services, LLC. All rights reserved. MongoDB/Gin/Svelte/Tailwind, if you're interested. 99 little bugs in the code. Take one down, patch it around, 117 little bugs in the code...